SYSYMar 26, 2015

Observer design for position and velocity bias estimation from a single direction output

arXiv:1503.07680
Originality Synthesis-oriented
AI Analysis

Solves a practical estimation problem for systems with biased velocity sensors, but the approach is incremental.

The paper designs a nonlinear observer to estimate an object's position from direction and velocity measurements, handling constant velocity bias with global exponential convergence under persistent excitation.

This paper addresses the problem of estimating the position of an object moving in $R^n$ from direction and velocity measurements. After addressing observability issues associated with this problem, a nonlinear observer is designed so as to encompass the case where the measured velocity is corrupted by a constant bias. Global exponential convergence of the estimation error is proved under a condition of persistent excitation upon the direction measurements. Simulation results illustrate the performance of the observer.

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